We use the model GAMAVI as a case study to highlight the improvement of the multiple interface in comparison with the older.

%To verify the objectives of above theoretical design, PAMS is used as a most typical. The current version of PAMS is designed by following this construction. To apply this conception to PAMS, beside defining a DTD structure and XML file for a multiple interface, it is important to chose the available technologies that are used to developing PAMS such as JAVA, Enterprise Java Bean, JSP \cite{PAMS:2008}... to program the necessary entities to use this construction. After that, we represent the model GAMAVI as a case study to compare the new improvement with the older.
%

%\subsection{Integration of the multiple interface for PAMS platform}
%
%	We consider that the current version of PAMS suggests a more fully participatory simulation. Currently, PAMS provides a common interface for all participants to simulate with collaborative tools like video conference, white-board, instant message on which they communicate and discuss. The generic design found that a participatory simulation should have a custom interface. This means should specialize the role of each participant whose view and control of the parameters and outputs of the simulation are different. Interface of current PAMS comprises a parameter panel to initialize and modify parameters of a model, a control panel to run the simulation model, a display panel to observe the process of simulation, a monitor panel to view variable values. Integration of the multiple interface for PAMS platform is the same with we specialize these panels for each role. Each panel remains some elements they need.
%	
%To build the interface, at first it should make the design, the definition. After that, they assign different roles of a simulation model to participants as the above generic concept. Each role gives the individual rights of controlling or observing the parameters and outputs.
%	
%Our work focus on three main parts: the first part is to build a general language based on XML structure to define the interface of each individual participant. This file will describe the parameters, the monitors, the displays and the graphs of a model that will be visible and controllable elements. XML is a good strategy to easily combine different modules without problem compatible. The second part is to allow the user to upload the XML file on PAMS. The third part is to build a module EJB with an XML parser to change the old interface for the new with the above specification XML file. This interface is called specialized interface.


\subsection{Case study}

Here, we represent the GAMAVI model, which aim to understand and evaluate the impact of the environment on the dynamic of avian influenza among poultry flocks in North Vietnam at the village scale. The simulation has been implemented on the GAMA simulator \cite{Amouroux:2010}. This model provides an apparatus that allows epidemiologists to
build fully controlled experiments in order to test and explore hypotheses that could neither be conducted on the field nor in laboratory. Practically, the experiments focus on the influence of the poultry production, the environment (topography and dynamics) and their interactions \cite{Amouroux:2010}.

%This schema contains four roles in a participatory simulation with an extraction of their rights. The cooperation of these thematicians influence the sphere and the measure of propagation.
% Je ne comprends pas trop les 2 phrases au dessus, je propose quand meme:
Figure \ref{fig:Fig5} present an example of XML configuration file for the GAMAVI model. And Figure \ref{fig:Fig5_1} show a curtailed interface of PAMS that is the result of the integration of XML role file to GAMAVI model on PAMS. You can see that each participant, who have a personal role under the distribution of modellers, can only modify theirs correspond parameters and observe only theirs displays that are detailed in XML role file for this model. Moreover, monitors and graphs of each role have the same custom with displays. In this participatory version of GAMAVI, there are three roles with different visualization and access rights:
% The cooperation of these thematicians will improve the realism of the simulation and the understanding of the dynamics of the system for each of them.
%
\begin{figure}[!t]
\centering
\includegraphics[width=\linewidth]{imgs/Fig5-code}
\caption{XML role file for GAMAVI model on GAMA}
\label{fig:Fig5}
\end{figure}

\begin{figure}[!t]
\centering
\includegraphics[width=\linewidth]{imgs/Fig5-interface}
\caption{Curtailed participatory interface of PAMS}
\label{fig:Fig5_1}
\end{figure}

\begin{itemize}
    \item \emph{Local\_Authority}: accesses only to parameters and outputs related to natural and social characteristics of their village;
    \item \emph{Epidemiologist}: accesses only to parameters and outputs related to the epidemiology;
    \item \emph{Farmer}: accesses only to parameters and outputs on the movement of poultry and on the production dynamics (\emph{i.e.} periodicity of renewal).
\end{itemize}	

Practically, the local authorities provide the statistical data about natural and social characteristics of the village while epidemiologists have data and hypotheses on the epidemics dynamics. Natural data include topography of the environment, temperature and seasonality. Social characteristics of a village consist mainly of the number and types of farms and the organization and the dynamics of the production. Epidemics are mostly described using direct infectiousness, persistence in the environment and disease consequences on the individual (morbidity, mortality, duration of infection and so on). In addition, epidemiologists have the theoretical background required to understand the dynamics of the disease and to evaluate which parameters have to be changed in order to mitigate the virus diffusion and which mitigation measures are possible to do the same. Finally, farmers are experts of poultry production dynamics (farm management) and daily behaviors of the poultries (pasture, rest, movement, etc.).
	
The collaboration between these thematicians is important and actually necessary. Indeed, an expert of a domain will see many difficulties if he has no support from experts of other domains. His decision and correction on the simulation would not approach to reality.
% cette dernière phrase est pas top mais je ne trouve pas mieux en ce moment


\subsection{Benefits of the multiple interface}

Multi-agent systems are designed to study phenomena concerning a community of individual by modeling individual behaviors. Guyot \emph{et al.} \cite{GUYOT:2006} merged multi-agent systems and role playing games under the term of participatory multi-agent simulations by modeling collective behaviors. Therefore, an interface aiming at being very useful for participatory simulation must support the collaboration amongst experts to explore the collective behavior and the interaction between an expert and an agent to improve agents behaviors. With the current interface of the PAMS, it is difficult for actors to model accurately the behavior of each agent because the interface is not specialized for each participants' role. We cannot really get the best behavior if the interface does not allow experts to choose the best decisions. Moreover, the behaviors in the individual context are different from in the collective context. Indeed, in an individual context, one participant gives his decision only according knowledge in his specialized field of expertise  such as the local authorities, the epidemiologists, and the farmers in model GAMAVI. Thanks to their individual experiences, results of the teamwork are better. In a collective context, the decision of a participant can influence the decisions of the others. For example, the parameter of the water volume (controlled by the local authority) influences to compute the concentration of virus or ponds depletion rate (realized by the epidemiologist).

In addition to the possibility to explore collective behaviors, the multiple interface added in PAMS is also very important during the the development of the simulator. Indeed, the maturity of the agent behavior directly affects the outcome of the simulation \cite{GUYOT_THESE:2006}. In the model GAMAVI, if only the epidemiologists participate to the simulation development by tackling only the reasons of the propagation of the H5N1 virus, they cannot get reliable results: they cannot understand the behavior and the structures of poultries, they do not participate to pasture these poultries. They only have knowledge on epidemic.

A multi-agent participatory simulation often includes three kinds of actors: thematicians (or domain experts), modelers and computer scientists. 
% In fact, negotiations between the computer scientist and the domain expert to design the phenomenon.
% tu parles de thematicien puis de domain-expert ???
The role of the thematician is to execute and analyze the model. A multiple interface allows thematicians in the executive phase to play a particular role to validate and improve the simulation \cite{GUYOT_AAMAS:2006}; this phase is often the place  for negotiations. The above scenarios show that the multi-agent simulations provide a participatory method for exploring and studying collective behavior. The use of negotiation between multidisciplinary participants can help to explicit the individual behaviors on collaborative context \cite{GUYOT_THESE:2006}. These results are based on discussions after the experiments. If we construct a mechanism to trace and record all interactive changes of motivations of the agent, we can obtain and analyze the results and then extract meaningful consequences. After that we could construct a cognitive agent (with learning machine) and an assistant agent for a more complete participatory simulation. The verbalization phase will use these results to improve the paregoric quality and the decision-making quality. The collective behavior that can be extracted from playing and exchanging the roles formalize better individual strategies such as in \cite{GUYOT_AAMAS:2006}, \cite {Minh:2008} or \cite {Becu:2006}. In the GAMAVI, the negotiation amongst the farmers help to discover a better solution to isolate effectively the flocks of a farmer and the flocks of neighborhoods.

The different roles use to test and implement the methods that benefit in other disciplines. The research of behavior of agents in mixed communities is very important. It is necessary to resolve rivalries in a collective community. The work presented here constitutes a first step in the design of participatory agent-based simulations between members of the community. Each participant will take his responsibility and become an agent or set of agents. 